Digital tuning engine for highly programmable delta-sigma analog-to-digital converters

ABSTRACT

An integrated circuit includes a component calculator configured to compute at least one component value of a highly programmable analog-to-digital converter (ADC) from at least one application parameter, and a mapping module configured to map the component value to a corresponding register setting of the ADC based on at least one process parameter, wherein the integrated circuit produces digital control signals capable of programming the ADC. In a specific embodiment, the component calculator uses an algebraic function of a normalized representation of the application parameter to approximately evaluate at least one normalized ADC coefficient. The component value is further calculated by denormalizing the normalized ADC coefficient. In another specific embodiment, the component calculator uses an algebraic function of the application parameter to calculate the component value. In some embodiments, the integrated circuit further includes a scaling module configured to scale the component value based on scaling parameters.

FIELD OF THE DISCLOSURE

This disclosure relates in general to the field of electronic devicesand, more particularly, to a digital tuning engine for highlyprogrammable sigma-delta analog-to-digital converters (ADCs).

BACKGROUND

The delta-sigma (Δ-Σ) ADC (or, equivalently, sigma-delta (Σ-Δ) ADC) istypically used in modern voice-band, audio, and high-resolutionprecision industrial measurement applications. As used herein, the term“ADC” includes any device, electrical/electronic circuit, or integratedcircuit that can convert a continuous physical electrical quantity(e.g., voltage, current) to a digital number that can represent thequantity's amplitude (or other property). The Δ-Σ ADC is generally usedto convert analog signals over a relatively narrow range of frequencies,typically less than 5% of the ADC's sample rate. With currenttechnology, it is possible to support a sample rate of several GHz andthus Δ-Σ ADCs typically support bandwidths less than 200 MHz. Withbandpass Δ-Σ ADCs, this bandwidth may be located at frequencies that aresubstantial fractions of the sample rate, namely from direct current(DC) to several hundred megahertz. A typical Δ-Σ ADC comprises anoversampling modulator followed by a digital decimation filter thattogether produce a high-resolution data stream output. Auser-programmable Δ-Σ ADC is typically used to configure the ADC for aparticular application. For example, an ADC used in a receiver formulti-carrier GSM (global system for mobile communications) mightrequire a bandwidth of 40 MHz at an intermediate frequency (IF) of 180MHz, whereas an ADC used in a long term evolution (LTE) receiver mightrequire a bandwidth of 75 MHz at an IF of 300 MHz.

SUMMARY OF THE DISCLOSURE

An integrated circuit includes a component calculator configured tocompute at least one component value of a highly programmableanalog-to-digital converter (ADC) from at least one applicationparameter, and a mapping module configured to map the component value toa corresponding register setting of the ADC based on at least oneprocess parameter, wherein the integrated circuit produces digitalcontrol signals capable of programming the ADC. As used herein, the term“highly programmable ADC” comprises an ADC configured to havesubstantially continuously programmable bandwidth and center frequencyover a substantial range (e.g., factor of two). As used herein, the term“register setting” comprises values of bits in one or more controlregisters of the ADC. In some embodiments, the integrated circuitfurther includes a scaling module configured to scale the componentvalue based on scaling parameters. The scaling parameters can include afirst set of parameters for state scaling and a second set of parametersfor admittance scaling.

In a specific embodiment, the component calculator uses an algebraicfunction of a normalized representation (e.g., scaled relative to aparameter, such as sampling frequency) of the application parameter toapproximately evaluate at least one normalized ADC coefficient.Algebraic functions include algebraic expressions built from constants,variables, and a finite set of algebraic operations (e.g., addition,subtraction, multiplication, division, exponentiation, etc.). Thecomponent value is further calculated by denormalizing the normalizedADC coefficient. In a specific embodiment, the algebraic functioncomprises a polynomial function. In some embodiments, the applicationparameter comprises a center frequency of the ADC, and the normalizedrepresentation of the application parameter comprises a ratio of thecenter frequency and a sampling frequency. In another specificembodiment, the component calculator uses an algebraic function of theapplication parameter to calculate the component value.

In some embodiments, the component calculator, the scaling module, andthe mapping module are realized on a microprocessor. In someembodiments, the integrated circuit can include the ADC.

BRIEF DESCRIPTION OF THE DRAWINGS

To provide a more complete understanding of the present disclosure andfeatures and advantages thereof, reference is made to the followingdescription, taken in conjunction with the accompanying figures, whereinlike reference numerals represent like parts, in which:

FIG. 1 is a simplified block diagram of a system including a digitaltuning engine for highly programmable Δ-Σ ADCs in accordance with oneembodiment;

FIG. 2 is a simplified block diagram of example details of the systemaccording to one or more embodiments;

FIG. 3 is a simplified circuit diagram of other example details of anexample Δ-Σ ADC according to one embodiment;

FIG. 4 is a simplified block diagram illustrating other example detailsof an embodiment of the system;

FIG. 5 is a simplified block diagram illustrating example detailsassociated with an embodiment of the system;

FIG. 6 is a simplified block diagram illustrating other example detailsassociated with an embodiment of the system;

FIG. 7 is a simplified flow diagram illustrating example operations thatmay be associated with an embodiment of the system;

FIG. 8 is a simplified flow diagram illustrating other exampleoperations that may be associated with an embodiment of the system; and

FIG. 9 is a simplified flow diagram illustrating yet other exampleoperations that may be associated with an embodiment of the system.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

The present disclosure provides for a digital tuning engine for highlyprogrammable Δ-Σ ADCs in accordance with some embodiments. In general,programmable ADCs include control registers for configuring the ADC.These registers are typically non-memory mapped and are accessible onlyvia read and write commands. Typical, programmable ADCs that are capableof a high degree of tunability, for example, to support several modes ofoperation, have appropriate register settings pre-computed, hard-codedand unchangeable during operation (e.g., in real time, during use, orbetween uses). For example, AD9368 from Analog Devices, Inc. includes aprogrammable ADC with hard-coded register settings that allow supportinga few finite modes of operation. To support multiple modes of operation,the register settings are generated using external software and thenpassed to the ADC system prior to operations.

A typical programmable Δ-Σ ADC includes an attenuator or low noiseamplifier (LNA), both of adjustable gain, that can accept an analogsignal. The output of the LNA/attenuator can be coupled to a loop filtercomprising three resonators. The output of the loop filter may becoupled to a quantizer (e.g., flash ADC), and the output of thequantizer is fed back to the loop filter using a plurality ofdigital-to-analog converters (DACs). The loop filter's resistor andcapacitor values, the feedback DACs' currents, the flash's full-scale,the LNA/attenuator's settings, the amplifiers' bias currents and therelative timing of the flash and DACs are typically digitallyprogrammable. With programmable amplifier bias currents, 8-bitresolution on the DAC currents, resistor values, flash full-scale and upto 12-bit resolution on capacitors, there can be more than 500 controlbits (e.g., associated with the register settings) to be pre-computedfor configuring the ADC appropriately for a particular application.

However, it may be desirable to generate the ADC register settingsdynamically (e.g., during operation of the ADC, prior to using the ADCfor a specific application, using the ADC for different applicationswith register settings changed in-between the applications, etc.).Generating the register settings dynamically can allow greaterflexibility and modularity to use the ADC for a variety of applications,with little hassle from the user's point of view. In addition, theprogrammable nature of the ADC can provide the opportunity to compensatefor non-ideal effects or variation in component values from board toboard. As used herein, the term “component value” refers to the value ofa relevant property of an electronic component, such as capacitance of acapacitor; resistance or conductance of a resistor; inductance of aninductor; least significant bit (LSB) size of an ADC or DAC; etc.

Moreover, a highly-programmable Δ-Σ ADC has a large number of registersettings that can be complex functions of application parameters, suchas clock frequency, center frequency, bandwidth, full-scale, etc., andprocess parameters such as sheet resistance and capacitance per unitarea. Compounding this complexity are design parameters such as signalswing, stage impedance and NTF gain that can affect the performance ofthe Δ-Σ ADC. For example, a 6th order Δ-Σ ADC can have 20 registersettings with 8 or more bits of resolution, requiring elaborate softwarerunning on a desktop computer to compute the ADC register settings. Tomake such a Δ-Σ ADC more readily usable, a system, which can quicklytranslate user parameters into the ADC's digital control signals, isdesired.

Turning to FIG. 1, FIG. 1 is a simplified block diagram of a system 10comprising a digital tuning engine according to an example embodiment.System 10 includes a highly programmable Δ-Σ ADC 12 that can accept ananalog input and produce a digital output. In various embodiments,highly programmable Δ-Σ ADC 12 can include at least one analog loopfilter with programmable components, a quantizer whose input is coupledto an output of the analog loop filter, and one or more feedback DACswhose input is coupled to an output of the quantizer and whose output iscoupled to the analog loop filter. Highly programmable Δ-Σ ADC 12 canalso include at least four digital inputs that control variousparameters of Δ-Σ ADC 12, such as resistor and capacitor values withinthe loop filter, a least significant bit (LSB) size of the feedbackDACs, a LSB size of the quantizer, or power consumption of amplifiers.In various embodiments, the digital inputs may have fine enoughresolution to support a wide variety of clock frequencies, signalbandwidths, center frequencies, and/or power usages. Highly programmableΔ-Σ ADC 12 can have digital controls for a substantial fraction of itscomponents. The range of the controls may be sufficient to tune Δ-Σ ADC12 over at least an octave of frequency in sample rate or centerfrequency. In addition, the resolution of the controls may be sufficientto provide essentially continuous coverage of the octave in sample rateor center frequency.

A digital tuning engine 14 may be electrically connected to Δ-Σ ADC 12,and can accept application parameters 16 and process parameters 18. Asused herein, the term “application parameters” includes parameters(e.g., measurable factors, vectors, quantities, characteristics,aspects, features, etc.) that substantially influence the performance ofthe Δ-Σ ADC (e.g., Δ-Σ ADC 12) in a specific application (e.g., use towhich the Δ-Σ ADC is put, such as instrumentation/measurement,voice-band, audio, etc.); examples of application parameters include,without limitation, clock frequency, center frequency, bandwidth, powerconsumption, and/or the value of external components (e.g., resistors,capacitors, inductors, etc.). In some embodiments, applicationparameters 16 may be determined from specifications of the relevantapplication, electronic device, or electronic system in which Δ-Σ ADC 12is to be used. In some embodiments, application parameters 16 caninclude scaling parameters for state-scaling and admittance scaling.

The term “process parameters” includes parameters that indicatedeviations from nominal values for components associated with the Δ-ΣADC (e.g., Δ-Σ ADC 12); process parameters can include calibrated valuesof certain properties of the Δ-Σ ADC; examples of process parametersinclude, without limitation, capacitance per unit area, sheetresistance, parasitic resistance and comparator offset. In particular,process parameters can include a collection of information that, forcapacitors, can define a zero-code capacitance (e.g., capacitance for azero register setting in the Δ-Σ ADC; base capacitance) and capacitanceper code (e.g., register setting of the Δ-Σ ADC), and similarinformation for programmable conductances. In some embodiments, processparameters 18 may be determined by testing Δ-Σ ADC 12 under appropriatetest conditions (e.g., during manufacturing), simulated applicationconditions, or by calibrating Δ-Σ ADC 12 appropriately. In someembodiments, process parameters 18 may be determined in an on-demandfashion using dedicated calibration circuits on an integrated circuitimplementing Δ-Σ ADC 12.

In some embodiments, application parameters 16 and process parameters 18may be stored in a suitable memory element accessible by digital tuningengine 14. In other embodiments, application parameters 16 and processparameters 18 may be provided to digital tuning engine 14 directly by auser, for example, through appropriate software, commands, instructions,electronic signals, etc. In yet other embodiments, applicationparameters 16 and process parameters 18 may be provided to digitaltuning engine 14 by appropriate software, external device, etc., forexample, upon trigger of certain predetermined conditions.

According to various embodiments, in response to a tuning request 20(e.g., a “go” message from a user; an electronic signal that can turn ondigital tuning engine 14; a specific message from a user, externaldevice, application software, etc., instructing digital tuning engine 14to perform its operations), digital tuning engine 14 can convertapplication parameters 16 and process parameters 18 to ADC controlsignals 22, which may be applied to Δ-Σ ADC 12. In a specificembodiment, ADC control signals 22 may comprise digital signals. ADCcontrol signals 22 can configure Δ-Σ ADC 12 to operate according to aspecific set of application parameters 16 (e.g., specific clockfrequency, center frequency, bandwidth, power usage, etc.). In someembodiments, ADC control signals 22 may remain static upon completion ofthe tuning operation (e.g., after generation of ADC control signals 22)until a new tuning request 20 is made.

According to various embodiments, application parameters 16 can beconverted to unscaled component values using direct formulae or acombination of normalized formulae and denormalization. In someembodiments, unscaled component values may be scaled for swing and/orimpedance level, as appropriate. The component values may be mapped tocontrol register settings in accordance with process parameters 18.

In some embodiments, digital tuning engine 14 and Δ-Σ ADC 12 may berealized (e.g., implemented) on a single integrated circuit. In otherembodiments, digital tuning engine 14 and Δ-Σ ADC 12 may be realized inseparate integrated circuits. For example, digital tuning engine 14 maybe implemented on a microprocessor electrically connected to Δ-Σ ADC 12.

Turning to FIG. 2, FIG. 2 is a simplified block diagram illustratingexample details of an embodiment of digital tuning engine 14. Digitaltuning engine 14 may comprise a component calculator 30 that includes adenormalized formulae module 32, a normalized formulae module 34 thatreceives normalization data 35, and a denormalize module 36. In someembodiments, normalization data 35 may be stored in a separate databaserealized on a non-volatile memory (NVM). The NVM may also store softwarethat, when executed (e.g., on a suitable microprocessor), performsoperations of digital tuning engine 14. In some embodiments, the NVM mayalso store a tuning table comprising process parameters 18.

Component calculator 30 may be configured to receive applicationparameters 16 and compute component values (e.g., values of capacitance,inductance, conductance, current, etc. associated with capacitors,inductors, resistors, feedback DACs, etc.). In some embodiments, thecomputed component values may be in a form of unscaled component values38. Normalized formula module may use an algebraic function of anormalized representation of the application parameter to approximatelyevaluate normalized ADC coefficients. Unscaled component values 38 maybe calculated by denormalizing the normalized ADC coefficients.Denormalized formulae module 32 may use algebraic functions ofapplication parameters to calculate the component values directly (e.g.,without normalizing).

In general terms, unscaled component values 38 may be computed viaalgebraic functions of application parameters 16. Using well-knownprocedures, scaled delta sigma modulator realizations for a given ADCarchitecture may be calculated apriori (e.g., using suitable algorithmsoffline) and stored (e.g., hardcoded, saved in memory, etc.) in the NVM,and retrieved as normalization data 35. The use of normalization canallow for reduction in dimensions of the storage element that storesnormalization data 35. In one example, by dividing by frequencies (e.g.,sampling frequency F_(s)), normalization can be achieved to yield scaleddelta sigma modulator realizations (that can be stored as normalizationdata 35) in terms of normalized center frequency f₀=F_(s) and normalizedbandwidth bw=BW/F_(s), where F₀, F_(s) and BW are the center frequency,sampling frequency, and bandwidth, respectively according to applicationparameters 16. Curve-fitting can yield approximate expressions for eachof the components or coefficients in Δ-Σ ADC 12. For example, a suitablepolynomial may be used to approximate the normalized functions. Thepolynomial coefficients may be determined apriori and stored along withthe tuning software in NVM and accessed as part of normalization data35.

In some embodiments, optional steps comprising admittance scaling andswing scaling can be applied to unscaled component values 38 at scalingmodule 40. For example, swing-scaling can be controlled through X-scalevector 41 and admittance scaling can be controlled through Y-scalevector 41. X-scale vector 41 and Y-scale vector 41 are also referred toherein as scaling parameters 41). Scaling parameters 41 may be includedin application parameters 16 in some embodiments. X-scale vector 41 caninclude appropriate state-scaling factors for modulator states, withdefault state-scaling factor values being one. Increasing thestate-scaling factors can trade increased distortion or increasedsusceptibility to out-of-band signals for reduced noise. Admittancescaling can be controlled with Y-scale vector 41, which can includeadmittance-scaling factors for any integrators in Δ-Σ ADC 12. Scalingmodule 40 may scale unscaled component values 38 appropriately togenerate (scaled) component values 42.

According to various embodiments, mapping module 44 may map componentvalues 42 to appropriate register settings of Δ-Σ ADC 12 using processparameters 18. The register settings (e.g., register codes) may be alsoconstrained by ranges of allowable values for each specific component.If the desired component value falls outside the allowable range, amaximum or minimum value may be assigned. Alternatively, the componentcan be brought into the allowable range by adjusting the X-scale andY-scale vectors 41 associated with the component.

Turning to FIG. 3, FIG. 3 is a simplified circuit diagram illustratingan example highly programmable Δ-Σ ADC 12. Example highly programmableΔ-Σ ADC 12 includes integrators 50(1)-50(5), feedback DACs, andappropriate passive components, such as resistors and capacitors. In anLC mode, Δ-Σ ADC 12 has 20 control signals 22: 5 control signals for theintegrating capacitors (C₁, C₃, C₄, C₅, and C₆), 6 for the feedback DACsI₃, I₄, I₅, I₆, I₇, I₈), 7 for the internal conductances (G₃₁, G₄₃, G₃₄,G₅₃, G₅₄, G₆₅, G₅₆), 1 for the flash LSB and a LC buffer gain parameter(LC_buf_gain parameter). The coefficient calculation translates 13application and scaling parameters (e.g., 3 application parameters,including F_(ck) (clock frequency), F₀, BW); and 10 nominally-unityscaling parameters 41) into 20 ADC tuning parameters.

In various embodiments, component calculator 30 can approximate thenormalized tuning parameters with polynomial functions of the normalizedapplication parameters {f₀, bw}. The normalized tuning parameters may beconverted into ADC settings by a series of simple mathematicaloperations (e.g., addition, subtraction, multiplication, and division)and one or more conditional statements. For example, in a range ofinterest for the example Δ-Σ ADC 12 of the FIGURE, most of the ADCcoefficients (e.g., ADC coefficient refers to a ratio such as

$\frac{G_{ij}}{F_{s}C_{i}},\frac{I_{i}}{F_{s}C_{i}},$

etc. that may be associated with filter coefficients, filterperformance, LNA performance, etc. of the ADC) may be adequatelyapproximated by an example polynomial of the form:

p=a ₀₀ +a ₁₀ f ₀ +a ₂₀ f ₀ ² +a ₃₀ f ₀ ³ +a ₄₀ f ₀ ⁴ +bw(a ₀₁ +a ₁₁ f ₀+a ₂₁ f ₀ ²)

where p represents a normalized ADC coefficient, and a_(ij) representspolynomial coefficients. The example polynomial function is a 4th-orderpolynomial in f₀ with an added term comprising the normalized bandwidthbw multiplied by a 2nd-order polynomial in f₀. Each ADC coefficient inexample Δ-Σ ADC 12 can be described by its own polynomial function, anda collection of such polynomials (e.g., in the form of the polynomialcoefficient values and the polynomial function) may be stored in the NVMand accessed as part of normalization data 35. When an ADC coefficientsuch as

$\frac{G_{31}}{F_{s}C_{3}}$

ratio is to be computed, normalized formulae module 34 may evaluate theappropriate polynomial at the given bw and f₀. To obtain the G₃₁component value, denormalize module 36 may multiply the result of thepolynomial evaluation by appropriate component values and otherparameters such as C₃ and F_(s).

In various embodiments, denormalized formulae module 32 may useappropriate denormalized formulae to explicitly determine certain ADCcomponent values (e.g., G_(ij), C_(i), I_(i)) directly. For example, asthe inductor value L and center frequency F₀ is set in applicationparameters 16 (e.g., by the user), the value of C₁ follows directly fromthe following equation:

$C_{1} = \frac{1}{\left( {2\pi \; F_{0}} \right)^{2}L}$

Similarly, a direct calculation of the form C=a₁×F_(S)a₀ can providesufficient accuracy for the integrating capacitors when high-orderpolynomials are used to approximate the ADC coefficients. The values ofa₁ and a₀ may be determined by a linear curve-fit on a portion ofnormalization data 35 associated with scaled delta-sigma modulatorrealizations.

In some embodiments, additional steps may be applied to further refinethe computed component values. One example step uses knowledge about theresonant frequencies of second and third stage resonators with respectto bw and f₀. The resonance frequencies of resonators in the second andthird stages are provided according to the following equations,respectively:

$F_{02} = {\frac{1}{2\pi}\left( \sqrt{\frac{G_{34}\left( {- G_{43}} \right)}{C_{3}C_{4}}} \right)}$$F_{03} = {\frac{1}{2\pi}\left( \sqrt{\frac{G_{56}\left( {- G_{65}} \right)}{C_{5}C_{6}}} \right)}$

The relationships for resonance frequencies of the second and thirdstage resonators in the example Δ-Σ ADC 12 can be used to tweakcomponent values. For example, if the resonance frequency is high by 1%,C₅ and C₆ can be increased by 1% to compensate.

Another step to further fine-tune (e.g., refine, tweak) the computedcomponent values obtained via the polynomial formulae may be aimed atimproving the control of the Δ-Σ ADC 12's noise transfer function. Forexample, when Δ-Σ ADC 12 is configured as a bandpass ADC, the DC gain ofthe feedback path of the loop filter (L1_(dc)) may be controlledsuitably. L1_(dc) may be set accurately based on the DC gain of thenoise transfer function according to the following equation:

${NTF}_{dc} = \frac{1}{\left( {1 - {L\; 1_{dc}}} \right)}$

For a typical target value such as NTF_(dc)=3±10%, L1_(dc) may be0.67±5%, and at higher values of NTF_(dc) the L1_(dc) accuracyrequirement may be increasingly stringent. For the loop filter shown inthe example Δ-Σ ADC 12, L1_(dc) may be derived from a complex expressioninvolving many terms, which partially cancel, resulting in anill-controlled L1_(dc). Hence, to correct for the ill-controlledL1_(dc), one of the terms in L1_(dc), for example the term controlled byI₇, may be adjusted to match L1_(dc) with a target (e.g., desired)value. Specifically, I₇ may be computed from the following exampleequation:

$I_{7} = \frac{{L\; 1_{{DC}\mspace{11mu} {Target}}} - {L\; 1_{{{DC}\mspace{14mu} {with}\mspace{14mu} I_{7}} = 0}}}{R_{7}}$

For the highly-programmable example Δ-Σ ADC 12 of the FIGURE,swing-scaling can be controlled through appropriate Xscale vectors 41including the state-scaling factors for the six modulator states. Forexample, to accomplish state scaling on integrator 50(3) by X-scalevector 41, the coefficients associated with the input to integrator50(3), namely those corresponding to G₃₁, G₃₄ and I₃ can be multipliedby X-scale vector 41 and the coefficient(s) associated with the outputof integrator 50(3), namely G₄₃, would be divided by the same X-scalevector 41.

Similarly, admittance scaling can be controlled through appropriateY-scale vectors 41 including admittance-scaling factors for the fourbackend integrators 50(3)-50(6). For example, a first Y-scale vector 41(e.g., Yscale(1)) may multiply the integrating capacitance C₃, thefeedback current I₃ and the input conductances (G₃₁, G₃₄) of integrator50(3). Setting Yscale(1) to a value greater than one can reduce thenoise of integrator 50(3) but could increase the output current demandof its amplifier and all the amplifiers, which drive integrator 50(3).

Mapping module 44 may map computed component values 42 to appropriateregister settings of highly-programmable example Δ-Σ ADC 12 of theFIGURE. For example, the value of C1 is governed by the followingequation:

C ₁ =C ₁₀ +C _(1u) ×REC

where REG is a register setting corresponding to C₁, and C₁₀ (e.g., basecapacitance) and C_(1u) are included in process parameters 18 and may beprocess-dependent and determined by suitable calibration procedures.

Turning to FIG. 4, FIG. 4 is a simplified block diagram illustratingexample details associated with scaling parameters 41 related to examplehighly-programmable example Δ-Σ ADC 12 of FIG. 3. Scaling parameters 41can include X-scale vectors 52(1)-52(6). X-scale vector 52(1) maymultiply an allowable voltage swing of the LC tank 53. X-scale vector52(2) may multiply the current-swing in the inductor 54 and, hence, alsomultiply the full-scale current appropriately. X-scale vectors52(3)-52(6) may multiply voltage swing of integrators 55. IncreasingX-scale parameters 52(1)-52(6) may trade increased distortion orincreased susceptibility to out-of-band signals for reduced noise.

Turning to FIG. 5, FIG. 5 is a simplified block diagram showing exampledetails associated with scaling parameters 41 related to examplehighly-programmable example Δ-Σ ADC 12 of FIG. 3. Scaling parameters 41can include Y-scale vectors 56(1)-56(4). Y-scale vector 56(1) mayinclude admittance scaling factors for integrator 50(1); Y-scale vector56(2) may include admittance scaling factors for integrator 50(2);Y-scale vector 56(3) may include admittance scaling factors forintegrator 50(3); and Y-scale vector 56(4) may include admittancescaling factors for integrator 50(4).

Turning to FIG. 6, FIG. 6 is a simplified block diagram illustratingexample details of an embodiment of system 10. System 10 can include amicroprocessor 60 (e.g., ARM Cortex MO) and an address mapping module 62that interfaces with highly-programmable Δ-Σ ADC 12. Address mappingmodule 62 can be configured to receive application parameters 16,process parameters 18 and tuning request 20. The component calculationof component calculator 30, scaling operations of scaling module 40, andmapping operations of mapping module 44 may be implemented with softwareusing microprocessor 60. Hence, component calculator 30, scaling module40, and mapping module 44 may be realized appropriately onmicroprocessor 60.

Address mapping module 62 can handle data interactions and allowmicroprocessor 60 to treat the data interactions as simple memory readsand writes. In some embodiments, the procedures handled by the softwarecan be implemented using floating point representation. In otherembodiments, the software can be programmed using fixed-pointrepresentation, for example, to reduce the amount of memory and numberof libraries used to execute the software.

Turning to FIG. 7, FIG. 7 is a simplified flow diagram illustratingexample operations 100 that may be associated with component calculator30 of digital tuning engine 14 according to embodiments of system 10. At102, application parameters 16 may be received at digital tuning engine14. At 104, a determination may be made whether normalized formula isappropriate to calculate a specific component value. If not, at 106,appropriate denormalized formula may be used to compute the relevantunscaled component value. At 108, resonant frequency may be used torefine the calculated component value. At 110, the unscaled componentvalue may be obtained from the denormalized formula and resonantfrequency refinements.

Turning back to 104, if the normalized formula is appropriate for thespecific component, at 112, polynomial coefficients of the relevantpolynomial functions may be retrieved as part of normalization data 35.At 114, normalized ADC coefficients may be computed, for example, bysubstituting values of suitable application parameters 18 into thepolynomial function. At 116, the normalized ADC coefficients may bedenormalized to compute the relevant component value. At 118, thecomputed values may be refined, for example, to improve ADC noisetransfer function. The operations may step back to 108, and proceedthereafter.

Turning to FIG. 8, FIG. 8 is a simplified flow diagram illustratingexample operations 150 that may be associated with mapping module 44 ofdigital tuning engine 14 according to embodiments of system 10. At 152,process parameters 18 may be retrieved. At 154, computed componentvalues 42 may be retrieved. At 156, register settings may be computedfrom process parameters 18 and computed component values 42. at 158, ADCcontrol signals 22 may be generated.

Turning to FIG. 9, FIG. 9 is a simplified flow diagram illustratingexample operations 170 that may be associated with digital tuning engine14 according to embodiments of system 10. At 172, normalized ADCcoefficients may be evaluated from algebraic functions of normalizedrepresentations (e.g., f₀, bw) of application parameters (e.g., F₀, BW,etc.). At 174, the evaluated ADC coefficients may be adjusted forresonant frequency. For example, the ADC coefficients may be adjusted toget a desired (e.g., target) value of the resonant frequencies of thevarious resonators in Δ-Σ ADC 12.

At 176, appropriate X-scale vectors 41 mat be applied to modifystate-scaling, if desired. At 178, back-end capacitances and loop-filterconductances may be computed (e.g., from denormalized formulae). At 180,suitable Y-scale vectors 41 may be applied to change back-end admittancescaling, if desired. At 182, component values to available range usingstage-by-stage admittance scaling, if possible. At 184, suitable tuningmodels may be used to convert capacitances and conductances into ADCregister settings. Component values may be limited to an available rangeand errors can be reported should limiting occur.

In the discussions of the embodiments above, the capacitors, inductors,ADCs, resistors, amplifiers, switches, digital core, transistors, and/orother components can readily be replaced, substituted, or otherwisemodified in order to accommodate particular circuitry needs. Moreover,it should be noted that the use of complementary electronic devices,hardware, software, etc. offer an equally viable option for implementingthe teachings of the present disclosure.

In one example embodiment, any number of electrical circuits of theFIGURES may be implemented on a board of an associated electronicdevice. The board can be a general circuit board that can hold variouscomponents of the internal electronic system of the electronic deviceand, further, provide connectors for other peripherals. Morespecifically, the board can provide the electrical connections by whichthe other components of the system can communicate electrically. Anysuitable processors (inclusive of digital signal processors,microprocessors, supporting chipsets, etc.), memory elements, etc. canbe suitably coupled to the board based on particular configurationneeds, processing demands, computer designs, etc. Other components suchas external storage, additional sensors, controllers for audio/videodisplay, and peripheral devices may be attached to the board as plug-incards, via cables, or integrated into the board itself.

In another example embodiment, the electrical circuits of the FIGURESmay be implemented as stand-alone modules (e.g., a device withassociated components and circuitry configured to perform a specificapplication or function) or implemented as plug-in modules intoapplication specific hardware of electronic devices. Note thatparticular embodiments of the present disclosure may be readily includedin a system on chip (SOC) package, either in part, or in whole. An SOCrepresents an integrated circuit (IC) that integrates components of acomputer or other electronic system into a single chip. It may containdigital, analog, mixed-signal, and often radio frequency functions: allof which may be provided on a single chip substrate. Other embodimentsmay include a multi-chip-module (MCM), with a plurality of separate ICslocated within a single electronic package and configured to interactclosely with each other through the electronic package. In various otherembodiments, the amplification functionalities may be implemented in oneor more silicon cores in Application Specific Integrated Circuits(ASICs), Field Programmable Gate Arrays (FPGAs), and other semiconductorchips.

It is also imperative to note that all of the specifications,dimensions, and relationships outlined herein (e.g., the number of ADCcontrol signals, the topology of the ADC, the order of the polynomialformulae, etc.) have only been offered for purposes of example andteaching only. Such information may be varied considerably withoutdeparting from the spirit of the present disclosure, or the scope of theappended claims. The specifications apply only to one non-limitingexample and, accordingly, they should be construed as such. In theforegoing description, example embodiments have been described withreference to particular processor and/or component arrangements. Variousmodifications and changes may be made to such embodiments withoutdeparting from the scope of the appended claims. The description anddrawings are, accordingly, to be regarded in an illustrative rather thanin a restrictive sense.

Note that the activities discussed above with reference to the FIGURESare applicable to any integrated circuits that involve signalprocessing, particularly those that can execute specialized softwareprograms, or algorithms, some of which may be associated with processingdigitized real-time data. Certain embodiments can relate to multi-DSPsignal processing, floating point processing, signal/control processing,fixed-function processing, microcontroller applications, etc.

In certain contexts, the features discussed herein can be applicable tomedical systems, scientific instrumentation, wireless and wiredcommunications, radar, industrial process control, audio and videoequipment, current sensing, instrumentation (which can be highlyprecise), and other digital-processing-based systems. Moreover, certainembodiments discussed above can be provisioned in digital signalprocessing technologies for medical imaging, patient monitoring, medicalinstrumentation, and home healthcare. This could include pulmonarymonitors, accelerometers, heart rate monitors, pacemakers, etc. Otherapplications can involve automotive technologies for safety systems(e.g., stability control systems, driver assistance systems, brakingsystems, infotainment and interior applications of any kind).Furthermore, power-train systems (for example, in hybrid and electricvehicles) can use high-precision data conversion products in batterymonitoring, control systems, reporting controls, maintenance activities,etc.

In yet other example scenarios, the teachings of the present disclosurecan be applicable in the industrial markets that include process controlsystems that help drive productivity, energy efficiency, andreliability. In consumer applications, the teachings of the signalprocessing circuits discussed above can be used for image processing,auto focus, and image stabilization (e.g., for digital still cameras,camcorders, etc.). Other consumer applications can include audio andvideo processors for home theater systems, DVD recorders, andhigh-definition televisions. Yet other consumer applications can involveadvanced touch screen controllers (e.g., for any type of portable mediadevice). Hence, such technologies could readily part of smart-phones,tablets, security systems, personal computers (PCs), gamingtechnologies, virtual reality, simulation training, etc.

Note that with the numerous examples provided herein, interaction may bedescribed in terms of two, three, four, or more electrical components.However, this has been done for purposes of clarity and example only. Itshould be appreciated that the system can be consolidated in anysuitable manner. Along similar design alternatives, any of theillustrated components, modules, and elements of the FIGURES may becombined in various possible configurations, all of which are clearlywithin the broad scope of this Specification. In certain cases, it maybe easier to describe one or more of the functionalities of a given setof flows by only referencing a limited number of electrical elements. Itshould be appreciated that the electrical circuits of the FIGURES andits teachings are readily scalable and can accommodate a large number ofcomponents, as well as more complicated/sophisticated arrangements andconfigurations. Accordingly, the examples provided should not limit thescope or inhibit the broad teachings of the electrical circuits aspotentially applied to a myriad of other architectures.

Note that in this Specification, references to various features (e.g.,elements, structures, modules, components, steps, operations,characteristics, etc.) included in “one embodiment”, “exampleembodiment”, “an embodiment”, “another embodiment”, “some embodiments”,“various embodiments”, “other embodiments”, “alternative embodiment”,and the like are intended to mean that any such features are included inone or more embodiments of the present disclosure, but may or may notnecessarily be combined in the same embodiments.

Numerous other changes, substitutions, variations, alterations, andmodifications may be ascertained to one skilled in the art and it isintended that the present disclosure encompass all such changes,substitutions, variations, alterations, and modifications as fallingwithin the scope of the appended claims. In order to assist the UnitedStates Patent and Trademark Office (USPTO) and, additionally, anyreaders of any patent issued on this application in interpreting theclaims appended hereto, Applicant wishes to note that the Applicant: (a)does not intend any of the appended claims to invoke paragraph six (6)of 35 U.S.C. section 112 as it exists on the date of the filing hereofunless the words “means for” or “step for” are specifically used in theparticular claims; and (b) does not intend, by any statement in thespecification, to limit this disclosure in any way that is not otherwisereflected in the appended claims.

What is claimed is:
 1. An integrated circuit, comprising: a componentcalculator configured to compute at least one component value of ahighly programmable analog-to-digital converter (ADC) from at least oneapplication parameter; and a mapping module configured to map thecomponent value to a corresponding register setting of the ADC based onat least one process parameter, wherein the integrated circuit producesdigital control signals capable of programming the ADC.
 2. Theintegrated circuit of claim 1, further comprising a scaling moduleconfigured to scale the component value based on scaling parameters. 3.The integrated circuit of claim 2, wherein the scaling parameterscomprise a first set of parameters for state scaling and a second set ofparameters for admittance scaling.
 4. The integrated circuit of claim 2,wherein the component calculator, the scaling module, and the mappingmodule are realized on a microprocessor.
 5. The integrated circuit ofclaim 1, wherein the application parameter comprises a selection from agroup consisting of clock frequency, center frequency, samplingfrequency, bandwidth, and power consumption of the ADC, and wherein theprocess parameter comprises calibration information associated with theADC.
 6. The integrated circuit of claim 1, wherein the componentcalculator uses an algebraic function of a normalized representation ofthe application parameter to approximately evaluate at least onenormalized ADC coefficient.
 7. The integrated circuit of claim 6,wherein the algebraic function comprises a polynomial function.
 8. Theintegrated circuit of claim 6, wherein the application parametercomprises a center frequency of the ADC, and wherein the normalizedrepresentation of the application parameter comprises a ratio of thecenter frequency and a sampling frequency.
 9. The integrated circuit ofclaim 6, wherein the component value is calculated by denormalizing thenormalized ADC coefficient.
 10. The integrated circuit of claim 1,wherein the component calculator uses an algebraic function of theapplication parameter to calculate the component value.
 11. Theintegrated circuit of claim 1, further comprising the ADC.
 12. A method,comprising: calculating a component value of a highly programmable ADCfrom at least one application parameter; mapping the component value toa corresponding register setting of the ADC based on at least oneprocess parameter; and generating digital control signals capable ofprogramming the ADC.
 13. The method of claim 12, further comprisingscaling the component value using scaling parameters.
 14. The method ofclaim 12, wherein the calculating comprises evaluating at least onenormalized ADC coefficient using an algebraic function of a normalizedrepresentation of the application parameter.
 15. The method of claim 14,wherein the algebraic function comprises a polynomial function.
 16. Themethod of claim 12, wherein the calculating comprises evaluating analgebraic function of the application parameter.
 17. One or morenon-transitory tangible media encoding logic that includes instructionsfor execution that when executed by a processor, is operable to performoperations comprising: calculating a component value of a highlyprogrammable ADC from at least one application parameter; mapping thecomponent value to a corresponding register setting of the ADC based onat least one process parameter; and generating digital control signalscapable of programming the ADC.
 18. The media of claim 12, furtherconfigured for scaling the component value using scaling parameters. 19.The media of claim 12, wherein the calculating comprises evaluating atleast one normalized ADC coefficient using an algebraic function of anormalized representation of the application parameter.
 20. The media ofclaim 12, wherein the calculating comprises evaluating an algebraicfunction of the application parameter.